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Crystalline materials used in technological applications are often complex assemblies composed of multiple phases and differently oriented grains. Robust identification of the phases and orientation relationships from these samples is crucial, but the information extracted from the diffraction condition probed by an electron beam is often incomplete. We have developed an automated crystal orientation mapping (ACOM) procedure which uses a converged electron probe to collect diffraction patterns from multiple locations across a complex sample. We provide an algorithm to determine the orientation of each diffraction pattern based on a fast sparse correlation method. We demonstrate the speed and accuracy of our method by indexing diffraction patterns generated using both kinematical and dynamical simulations. We have also measured orientation maps from an experimental dataset consisting of a complex polycrystalline twisted helical AuAgPd nanowire. From these maps we identify twin planes between adjacent grains, which may be responsible for the twisted helical structure. All of our methods are made freely available as open source code, including tutorials which can be easily adapted to perform ACOM measurements on diffraction pattern datasets.
Obsidian is volcanic glass that results from the rapid cooling of silica-rich melt. Nanoscale crystallites precipitate out of the melt prior to solidification and remain embedded in the amorphous matrix. These crystallites provide information on the flow kinetics and composition of the melt. Due to the sparsity and size of nanolites, studies often focus on supramicron crystallites. This research takes advantage of the conchoidal fracture of obsidian by knapping samples with nanometer-thin edges for transmission electron microscopy characterization. Nanolites in the amorphous matrix are studied using energy-dispersive spectroscopy (EDS) and electron diffraction. Certain alkali and alkaline-earth cations exhibit patterns of depletion near Fe-oxide nanolites. EDS is used to identify nanolites and variations in the composition of the matrix. Parallel beam diffraction and radial distribution function analysis of nearest-neighbor distances determine average bond lengths in the matrix near nanolites, showing that nanolites influence the nearby short-range ordering and atomic character of the matrix. Analysis reveals decreased mean nearest-neighbor distances in the matrix adjacent to nanolites compared to the bulk. Our methods exhibit the required sensitivity to detect variations in the composition and structure near nanolites, and our findings indicate that obsidian nanolites contribute to quantifiable localized changes in the amorphous structure.
Scanning transmission electron microscopy (STEM) is an extremely versatile method for studying materials on the atomic scale. Many STEM experiments are supported or validated with electron scattering simulations. However, using the conventional multislice algorithm to perform these simulations can require extremely large calculation times, particularly for experiments with millions of probe positions as each probe position must be simulated independently. Recently, the plane-wave reciprocal-space interpolated scattering matrix (PRISM) algorithm was developed to reduce calculation times for large STEM simulations. Here, we introduce a new method for STEM simulation: partitioning of the STEM probe into “beamlets,” given by a natural neighbor interpolation of the parent beams. This idea is compatible with PRISM simulations and can lead to even larger improvements in simulation time, as well requiring significantly less computer random access memory (RAM). We have performed various simulations to demonstrate the advantages and disadvantages of partitioned PRISM STEM simulations. We find that this new algorithm is particularly useful for 4D-STEM simulations of large fields of view. We also provide a reference implementation of the multislice, PRISM, and partitioned PRISM algorithms.
Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.
In the field of transmission electron microscopy, data interpretation often lags behind acquisition methods, as image processing methods often have to be manually tailored to individual datasets. Machine learning offers a promising approach for fast, accurate analysis of electron microscopy data. Here, we demonstrate a flexible two-step pipeline for the analysis of high-resolution transmission electron microscopy data, which uses a U-Net for segmentation followed by a random forest for the detection of stacking faults. Our trained U-Net is able to segment nanoparticle regions from the amorphous background with a Dice coefficient of 0.8 and significantly outperforms traditional image segmentation methods. Using these segmented regions, we are then able to classify whether nanoparticles contain a visible stacking fault with 86% accuracy. We provide this adaptable pipeline as an open-source tool for the community. The combined output of the segmentation network and classifier offer a way to determine statistical distributions of features of interest, such as size, shape, and defect presence, enabling the detection of correlations between these features.
Investigate an outbreak of coronavirus disease 2019 (COVID-19) among operating room staff utilizing contact tracing, mass testing for severe acute respiratory coronavirus virus 2 (SARS-CoV-2), and environmental sampling.
Operating room staff with positive SARS-CoV-2 molecular testing.
Epidemiologic and environmental investigations were conducted including contact tracing, environmental surveys, and sampling and review of the operating room schedule for staff-to-staff, staff-to-patient, and patient-to-staff SARS-CoV-2 transmission.
In total, 24 healthcare personnel (HCP) tested positive for SARS-CoV-2, including nurses (29%), surgical technologists (25%), and surgical residents (16%). Moreover, 19 HCP (79%) reported having used a communal area, most commonly break rooms (75%). Overall, 20 HCP (83%) reported symptomatic disease. In total, 72 environmental samples were collected from communal areas for SARS-CoV-2 genomic testing; none was positive. Furthermore, 236 surgical cases were reviewed for transmission: 213 (90%) had negative preoperative SARS-CoV-2 testing, 21 (9%) had a positive test on or before the date of surgery, and 2 (<1%) did not have a preoperative test performed. In addition, 40 patients underwent postoperative testing (mean, 13 days to postoperative testing), and 2 returned positive results. Neither of these 2 cases was linked to our outbreak.
Complacency in infection control practices among staff during peak community transmission of SARS-CoV-2 is believed to have driven staff-to-staff transmission. Prompt identification of the outbreak led to rapid interventions, ultimately allowing for uninterrupted surgical service.
Placements within high secure forensic hospitals consist of wards providing various different levels of relational security. They should form a coherent pathway through secure care, based on individual patient risks and needs. Moves to less secure wards within high secure forensic hospitals and moves on to lower secure hospital settings have rarely been systematically studied.
The aim of this study was to ascertain if placements within Broadmoor High Secure Hospital and moves from Broadmoor to medium secure hospitals corresponded to measures of violence risk, programme completion and recovery.
A 13-month prospective cohort study was completed. Patients (n = 142) were rated at baseline for violence risk (Historical, Clinical and Risk – 20), therapeutic programme completion and recovery (DUNDRUM tool) and overall functioning (Global Assessment of Functioning). Placements on the care pathway and moves on to medium secure hospitals were observed.
Placements on the care pathway within the high secure hospital were associated with dynamic violence risk (F = 16.324, P<0.001), therapeutic programme completion (F = 4.167, P = 0.003), recovery (F = 2.440, P = 0.050) with better scores on these measures being found in the rehabilitation wards and the poorest scores on the highest levels of dependency. Moves to medium secure hospitals were associated with better scores on dynamic risk of violence (F = 33.199, P<0.001), therapeutic programme completion (F = 9.237 P<0.001), recovery (F = 6.863, P = 0.001).
Placements within Broadmoor Hospital formed a coherent pathway through high secure care. Moves to less secure places were influenced by more than reduction in violence risk. Therapeutic programme completion and recovery in a broad sense were also important.
Item 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most positive responses are not associated with suicidality. The PHQ-8, which omits Item 9, is thus increasingly used in research. We assessed equivalency of total score correlations and the diagnostic accuracy to detect major depression of the PHQ-8 and PHQ-9.
We conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic accuracy.
16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard (N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (−0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies (N = 27), with similar results for studies that used other types of interviews (N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01).
PHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.
A national need is to prepare for and respond to accidental or intentional disasters categorized as chemical, biological, radiological, nuclear, or explosive (CBRNE). These incidents require specific subject-matter expertise, yet have commonalities. We identify 7 core elements comprising CBRNE science that require integration for effective preparedness planning and public health and medical response and recovery. These core elements are (1) basic and clinical sciences, (2) modeling and systems management, (3) planning, (4) response and incident management, (5) recovery and resilience, (6) lessons learned, and (7) continuous improvement. A key feature is the ability of relevant subject matter experts to integrate information into response operations. We propose the CBRNE medical operations science support expert as a professional who (1) understands that CBRNE incidents require an integrated systems approach, (2) understands the key functions and contributions of CBRNE science practitioners, (3) helps direct strategic and tactical CBRNE planning and responses through first-hand experience, and (4) provides advice to senior decision-makers managing response activities. Recognition of both CBRNE science as a distinct competency and the establishment of the CBRNE medical operations science support expert informs the public of the enormous progress made, broadcasts opportunities for new talent, and enhances the sophistication and analytic expertise of senior managers planning for and responding to CBRNE incidents.
Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.
To evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics.
Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit.
A total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15–3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98–10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7–15) (OR = 0.96; 95% CI = 0.56–1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26–0.97).
The MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.
Declaration of interest
Drs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain. Dr Chan is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD and Pfizer. She has received sponsorships and honorarium for giving lectures and providing consultancy and her affiliated institution has received research grants from these companies. Dr Hegerl declares that within the past 3 years, he was an advisory board member for Lundbeck, Servier and Otsuka Pharma; a consultant for Bayer Pharma; and a speaker for Medice Arzneimittel, Novartis, and Roche Pharma, all outside the submitted work. Dr Inagaki declares that he has received grants from Novartis Pharma, lecture fees from Pfizer, Mochida, Shionogi, Sumitomo Dainippon Pharma, Daiichi-Sankyo, Meiji Seika and Takeda, and royalties from Nippon Hyoron Sha, Nanzando, Seiwa Shoten, Igaku-shoin and Technomics, all outside of the submitted work. Dr Yamada reports personal fees from Meiji Seika Pharma Co., Ltd., MSD K.K., Asahi Kasei Pharma Corporation, Seishin Shobo, Seiwa Shoten Co., Ltd., Igaku-shoin Ltd., Chugai Igakusha and Sentan Igakusha, all outside the submitted work. All other authors declare no competing interests. No funder had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.
Using the Medical Priority Dispatch System (MPDS) – a systematic 911 triage process – to identify a large subset of low-acuity patients for secondary nurse triage in the 911 center is a largely unstudied practice in North America. This study examines the ALPHA-level subset of low-acuity patients in the MPDS to determine the suitability of these patients for secondary triage by evaluating vital signs and necessity of lights-and-siren transport, as determined by attending Emergency Medical Services (EMS) ambulance crews.
The primary objective of this study was to determine the clinical status of MPDS ALPHA-level (low-acuity) patients, as determined by on-scene EMS crews’ patient care records, in two US agencies. A secondary objective was to determine which ALPHA-level codes are suitable candidates for secondary triage by a trained Emergency Communication Nurse (ECN).
In this retrospective study, one full year (2013) of both dispatch data and EMS patient records data, associated with all calls coded at the ALPHA-level (low-acuity) in the dispatch protocol, were collected. The primary outcome measure was the number and percentage of ALPHA-level codes categorized as low-acuity, moderate-acuity, high-acuity, and critical using four common vital signs to assign these categories: systolic blood pressure (SBP), pulse rate (PR), oxygen saturation (SpO2), and Glasgow Coma Score (GCS). Vital sign data were obtained from ambulance crew electronic patient care records (ePCRs). The secondary endpoint was the number and percentage of ALPHA-level codes that received a “hot” (lights-and-siren) transport.
Out of 19,300 cases, 16,763 (86.9%) were included in the final analysis, after excluding cases from health care providers and those with missing data. Of those, 89% of all cases did not have even one vital sign indicator of unstable patient status (high or critical vital sign). Of all cases, only 1.1% were transported lights-and-siren.
With the exception of the low-acuity, ALPHA-level seizure cases, the ALPHA-level patients are suitable to transfer for secondary triage in a best-practices, accredited, emergency medical dispatch center that utilizes the MPDS at very high compliance rates. The secondary nurse triage process should identify the few at-risk patients that exist in the low-acuity calls.
ScottG, ClawsonJ, FivazMC, McQueenJ, GardettMI, SchultzB, YoungquistS, OlolaCHO. Using On-scene EMS Responders’ Assessment and Electronic Patient Care Records to Evaluate the Suitability of EMD-triaged, Low-acuity Calls for Secondary Nurse Triage in 911 Centers. Prehosp Disaster Med. 2016;31(1):46–57.
Few studies have investigated developmental strengths and weaknesses within the cognitive profile of children and adolescents with fragile X syndrome (FXS), a single-gene cause of inherited intellectual impairment. With a prospective longitudinal design and using normalized raw scores (Z scores) to circumvent floor effects, we measured cognitive functioning of 184 children and adolescents with FXS (ages 6 to 16) using the Wechsler Scale of Intelligence for Children on one to three occasions for each participant. Participants with FXS received lower raw scores relative to the Wechsler Scale of Intelligence for Children normative sample across the developmental period. Verbal comprehension, perceptual organization, and processing speed Z scores were marked by a widening gap from the normative sample, while freedom from distractibility Z scores showed a narrowing gap. Key findings include a relative strength for verbal skills in comparison with visuospatial–constructive skills arising in adolescence and a discrepancy between working memory (weakness) and processing speed (strength) in childhood that diminishes in adolescence. Results suggest that the cognitive profile associated with FXS develops dynamically from childhood to adolescence. Findings are discussed within the context of aberrant brain morphology in childhood and maturation in adolescence. We argue that assessing disorder-specific cognitive developmental profiles will benefit future disorder-specific treatment research.